Operating slide valves in petrochemical plants or refineries

ABSTRACT

A plant or refinery may include equipment such as condensers, regenerators, distillation columns, pumps, slide valves, or the like. Different operating methods may impact deterioration in equipment condition, thereby prolonging equipment life, extending production operating time, or providing other benefits. Mechanical or digital sensors may be used for monitoring equipment to determine whether problems are developing. Specifically, sensors may be used in conjunction with one or more system components to predict and detect slide valve sticking. A shielded, tube skin thermocouple assembly may provide a temperature profile for a slide valve. Tomography may be used to image a slide valve. An operating condition of the plant or refinery may be adjusted to prolong equipment life or avoid equipment failure.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of priority under 35 U.S.C. § 119(e)to U.S. Provisional Application No. 62/477,280, filed Mar. 27, 2017,which is incorporated by reference in its entirety.

FIELD

The present disclosure is related to a method and system for improvingthe performance of components that make up operations in a plant, suchas a carbonaceous processing plant, a chemical plant, a petrochemicalplant, or a refinery. Typical plants may be those that provide catalyticcracking or methanol oligomerization using a fluidized catalyst, or anyrefinery, petrochemical, or pyrolysis oil plant that circulates solids.

BRIEF DESCRIPTION OF DRAWINGS

The present disclosure is illustrated by way of example and not limitedin the accompanying figures in which like reference numerals indicatesimilar elements and in which:

FIG. 1 depicts an illustrative arrangement for a fluid catalyticcracking process in accordance with one or more example embodiments;

FIG. 2 depicts an illustrative cold wall slide valve in accordance withone or more example embodiments;

FIG. 3 depicts an illustrative hot wall slide valve in accordance withone or more example embodiments;

FIG. 4 depicts an illustrative flue gas double disc slide valve inaccordance with one or more example embodiments;

FIGS. 5A and 5B depict a plan view of a cold wall slide valve inaccordance with one or more example embodiments;

FIG. 6A depicts an orifice plate support having an orifice in accordancewith one or more example embodiments;

FIG. 6B depicts a disc in accordance with one or more exampleembodiments;

FIG. 7A depicts an illustrative orifice support plate that hasexperienced erosion;

FIG. 7B depicts an illustrative stem that has experienced erosion;

FIG. 8 depicts calibration for a slide valve actuator in accordance withone or more example embodiments;

FIG. 9 depicts a slide valve actuator system in accordance with one ormore example embodiments;

FIG. 10A depicts an illustrative computing environment for managing theoperation of one or more pieces of equipment in a plant in accordancewith one or more example embodiments;

FIG. 10B depicts an illustrative data collection computing platform forcollecting data related to the operation of one or more pieces ofequipment in a plant in accordance with one or more example embodiments;

FIG. 10C depicts an illustrative data analysis computing platform foranalyzing data related to the operation of one or more pieces ofequipment in a plant in accordance with one or more example embodiments;

FIG. 10D depicts an illustrative data analysis computing platform foranalyzing data related to the operation of one or more pieces ofequipment in a plant in accordance with one or more example embodiments;

FIG. 10E depicts an illustrative control computing platform forcontrolling one or more parts of one or more pieces of equipment in aplant in accordance with one or more example embodiments;

FIGS. 11A-11B depict an illustrative flow diagram of one or more stepsthat one more devices may perform in controlling one or more aspects ofa plant operation in accordance with one or more example embodiments;

FIGS. 12-13 depict illustrative graphical user interfaces related to oneor more aspects of a plant operation in accordance with one or moreexample embodiments; and

FIG. 14 depicts an illustrative flowchart of a process that one or moredevices may perform in controlling one or more aspects of a plantoperation in accordance with one or more example embodiments.

DETAILED DESCRIPTION

In the following description of various illustrative embodiments,reference is made to the accompanying drawings, which form a parthereof, and in which is shown, by way of illustration, variousembodiments in which aspects of the disclosure may be practiced. It isto be understood that other embodiments may be utilized, and structuraland functional modifications may be made, without departing from thescope of the present disclosure.

It is noted that various connections between elements are discussed inthe following description. It is noted that these connections aregeneral and, unless specified otherwise, may be direct or indirect,wired or wireless, and that the specification is not intended to belimiting in this respect.

A chemical plant or a petrochemical plant or a refinery may include oneor more pieces of equipment that process one or more input chemicals tocreate one or more products. Fluidized catalytic cracking (FCC) can beused to convert heavy gasoils into lighter distillate, naphtha, andchemical products.

A multitude of process equipment may be utilized in the chemical,refining, and petrochemical industry including, but not limited to,slide valves, rotating equipment, pumps, compressors, heat exchangers,fired heaters, control valves, fractionation columns, reactors, and/orshut-off valves.

Elements of chemical and petrochemical/refinery plants may be exposed tothe outside and thus can be exposed to various environmental stresses.Such stresses may be weather related, such as temperature extremes (hotand cold), high-wind conditions, and precipitation conditions such assnow, ice, and rain. Other environmental conditions may be pollutionparticulates, such as dust and pollen, or salt if located near an ocean,for example. Such stresses can affect the performance and lifetime ofequipment in the plants. Different locations may have differentenvironmental stresses. For example, a refinery in Texas may havedifferent stresses than a chemical plant in Montana.

Process equipment may deteriorate over time, affecting the performanceand integrity of the process. Such deteriorating equipment mayultimately fail, but before failing, may decrease efficiency, yield,and/or product properties. It is desirable that corrective actions betaken in advance of equipment inefficiencies and/or failure.

FIG. 1 shows a typical fluid catalytic cracking (FCC) process, whichincludes an FCC fluidized bed reactor and a spent catalyst regenerator.Regenerated cracking catalyst entering the reactor, from the spentcatalyst regenerator, is contacted with an FCC feed stream in a risersection at the bottom of the FCC reactor, to catalytically crack the FCCfeed stream and provide a product gas stream, comprising crackedhydrocarbons having a reduced molecular weight, on average, relative tothe average molecular weight of feed hydrocarbons in the FCC feedstream. As shown in FIG. 1, steam and lift gas are used as carrier gasesthat upwardly entrain the regenerated catalyst in the riser section, asit contacts the FCC feed. In this riser section, heat from the catalystvaporizes the FCC feed stream, and contact between the catalyst and theFCC feed causes cracking of this feed to lower molecular weighthydrocarbons, as both the catalyst and feed are transferred up the riserand into the reactor vessel. A product gas stream comprising the cracked(e.g., lower molecular weight) hydrocarbons may be separated from spentcracking catalyst at or near the top of the reactor vessel, preferablyusing internal solid/vapor separation equipment, such as cycloneseparators. This product gas stream, essentially free of spent crackingcatalyst, then exits the reactor vessel through a product outlet linefor further transport to the downstream product recovery section.

The spent or coked catalyst, following its disengagement or separationfrom the product gas stream, requires regeneration for further use. Thiscoked catalyst first falls into a dense bed stripping section of the FCCreactor, into which steam is injected, through a nozzle and distributor,to purge any residual hydrocarbon vapors that would be detrimental tothe operation of the regenerator. After this purging or strippingoperation, the coked catalyst is fed by gravity to the catalystregenerator through a spent catalyst standpipe. FIG. 1 depicts aregenerator, which can also be referred to as a combustor. Variousconfigurations of regenerators may be used. In the spent catalystregenerator, a stream of oxygen-containing gas, such as air, isintroduced to contact the coked catalyst, burn coke deposited thereon,and provide regenerated catalyst, having most or all of its initial cokecontent converted to combustion products, including CO2, CO, and H2Ovapors that exit in a flue gas stream. The regenerator operates withcatalyst and the oxygen-containing gas (e.g., air) flowing upwardlytogether in a combustor riser that is located within the catalystregenerator. At or near the top of the regenerator, following combustionof the catalyst coke, regenerated cracking catalyst is separated fromthe flue gas using internal solid/vapor separation equipment (e.g.,cyclones) to promote efficient disengagement between the solid and vaporphases.

In the FCC recovery section, the product gas stream exiting the FCCreactor is fed to a bottoms section of an FCC main fractionation column.Several product fractions may be separated on the basis of theirrelative volatilities and recovered from this main fractionation column.Representative product fractions include, for example, naphtha (or FCCgasoline), light cycle oil, and heavy cycle oil.

Other petrochemical processes produce desirable products, such asturbine fuel, diesel fuel and other products referred to as middledistillates, as well as lower boiling hydrocarbonaceous liquids, such asnaphtha and gasoline, by hydrocracking a hydrocarbon feedstock derivedfrom crude oil or heavy fractions thereof. Feedstocks most oftensubjected to hydrocracking are the gas oils and heavy gas oils recoveredfrom crude oil by distillation. For example, the conversion of methanolto olefins (MTO) produces ethylene and propylene from natural gas orcoal. MTO enables low costs of production for ethylene and propylene andproduces olefins at high ratios of propylene to ethylene than otherprocesses. Rapid thermal processing (RTP) (Ensyn's patented RTP®technology) utilizes renewable cellulosic biomass, typicallywood-derived feedstocks, in a thermal conversion process that produceshigh yields of free-flowing liquid biocrude. The technology utilizes aprocess similar to the FCC process but circulates an inert sand heatcarrier, instead of catalyst, to convert the biomass to a biocrude.

References herein to a “plant” are to be understood to refer to any ofvarious types of chemical and petrochemical manufacturing or refiningfacilities. References herein to a plant “operators” are to beunderstood to refer to and/or include, without limitation, plantplanners, managers, engineers, technicians, operators, and othersinterested in, overseeing, and/or running the daily operations at aplant.

Slide Valves

Some plants may include one or more slide valves, which may be connectedin series or in parallel with other pieces of equipment, and/or may beintegrated directly into a particular piece of equipment. Slide valvesmay be used in gravity flow applications of dry material, such ascatalysts aggregates (e.g., powder, pellets, or granulars). A slidevalve system may be of a variety of constructions depending on theprocess and types of aggregates. For example, there are regeneratedcatalyst slide valves, spent catalyst slide valves, and recirculationcatalyst slide valves. In addition, there are slide valves for gaseousstreams, such as flue gas slide valves, which are typically double discvalves.

A typical slide valve system may include a valve body. Inside the bodymay be an actuator to control the valve, including a piston, an orificeplate support, and a movable disc to cover or uncover the orifice. Theactuator is typically distinct from the slide valve body but mounted toit and coupled to it. The piston may operate to move the disc uponinitiation by the actuator.

A disc is a movable obstruction inside a stationary valve body thatadjustably restricts flow through the valve. Discs come in variousshapes such as disc-shapes and rectangular shapes. The disc may becoated with concrete or ceramic or other refractory material to protectthe disc. The disc generally closes and opens an orifice in a pipe orgravity feeder. Such orifice may be circular or rectangular. Thediameter or width of the discs may be 6″ to 48″, typically 24″ to 36″for petrochemical use. The valves may be operated to open or close thehole and/or may be used for volume metering.

Two discs may be used to block or allow flow for a gaseous stream, suchas a flue gas slide valve.

Guides may be used to guide the discs between opened and closedpositions. The guides may be positioned within the valve body adjacentthe orifice plate support to guide the disc in a linear direction acrossthe orifice.

An actuator is a mechanism or device to automatically or remotelycontrol a valve under a source of power. The actuator may be controlledby electricity using a motor or a solenoid. For example, an integratedactuator may include an electromechanical solenoid. An electromechanicalsolenoid is a specific type of relay to operate an electrical switch toinitiate action of a piston, for example.

The actuator may include a piston. A piston may be a pneumatic(pressurized air) or hydraulic (pressurized liquid) piston, and may beused to open or close the valve by pushing or pulling the disc intoposition. The actuator piston and associated instruments may be shieldedfrom the effects of radiant heat. For example, a shield may beconfigured to protect the actuator piston such that the actuator pistontemperature does not exceed a particular temperature (e.g., 150° F. (65°C.)). Alternatively or additionally, heating and/or cooling may beutilized, as required, to maintain satisfactory operation at ambientconditions. For example, a hydraulic fluid reservoir may be nitrogen gasblanketed.

An electro-hydraulic actuator assembly may be present for each valve ina process with individual hydraulic power sources. Double disc slidevalves may share one hydraulic power source. The piston may be directlyconnected to the slide valve to minimize the effects of backlash.Backlash is a relative movement between connected mechanical parts,resulting from looseness, when motion is reversed. This is sometimesalso referred to as slop, lost motion, or free play.

A stem, if present, may transmit motion from the controlling device(actuator/piston) to the disc. The stem may protrude through the bonnetwhen present. In some cases, the stem and the disc can be combined inone piece.

A bonnet may be attached to the valve body and may act as a cover toprotect the valve stem. The bonnet may be threaded, bolted, or weldedinto the valve body. The bonnet may be removable for maintenance.

Valve components may be made of carbon steel (CS), stainless steel (SS),duplex & super duplex stainless steels, titanium, zirconium, Uranus® B6,tantalum, nickel, Hastelloy®, and/or Monel. Construction methods mayinclude fabricated (welded), cast, and/or solid. Hot wall slide valvesare typically chrome alloys (ex. 1¼″ Cr-½ Mo).

A slide valve may be used under high and low pressure conditions, highand low temperature conditions, high abrasion, corrosive, and highviscosity conditions. In the petrochemical and related processes, suchslide valves may be used for solids, such as catalysts.

FIG. 2 depicts an example cold wall slide valve. Valve body 200 issurrounded by valve bonnet 210. Valve bonnet cover flange 214 isconnected to bonnet 210 via external bolting 212. The disc 228 ispositioned downstream of orifice 222. Valve stem 226 moves disc 228along orifice plate support 218 to open and close orifice 222. A highdensity refractory lining 220 covers body 200 internal surfaces. Guides(not shown in this figure) may guide the disc as it moves in a lineardirection to open and close the orifice.

FIG. 3 depicts an example hot wall slide valve. Valve body 300 issurrounded by valve bonnet 310. Valve bonnet cover flange 314 isconnected to bonnet 310 via external bolting 312. The disc 328 ispositioned downstream of orifice 322. Valve stem 326 moves disc 328along orifice plate support 318 to open and close orifice 322. A highdensity refractory lining 320 covers body 300 internal surfaces. Guides(not shown in this figure) may guide the disc as it moves in a lineardirection to open and close the orifice.

A slide valve for a fluidized catalytic cracking (FCC), methyl to olefin(MTO), rapid thermal processing (RTP), or other similar processes needsdurability against high temperature and powder (catalyst/sand) flow. Theslide valve's sliding surfaces may be hard-faced with overlaying. Theinner surface may have an abrasion resistant lining. The internal partsmay be designed to minimize erosion by catalyst. The valve may beprecise-controlled by electro-hydraulic actuators.

FIG. 4 depicts an example flue gas double disc slide valve. Valve body400 is surrounded by valve bonnet 410. Valve bonnet cover flange 414 isconnected to bonnet 410 via external bolting 412. The disc 428 ispositioned downstream of orifice 422. Valve stem 426 moves disc 428along orifice plate support 418 to open and close orifice 422. A highdensity refractory lining 420 covers body 400 internal surfaces. Guides(not shown) may guide the disc as it moves in a linear direction to openand close the orifice.

FIGS. 5A and 5B depict plan and elevation views, respectively, of a coldwall slide valve. As shown in FIG. 5A, the cold wall slide valve mayinclude guides 222 that disc 228 will slide between. A stuffing box 260is utilized for preventing leakage of gases or liquids along a movingrod or shaft at the point at which it leaves a cylinder. The bonnet 262is connected to actuator 264.

FIG. 6A depicts an orifice plate support having an orifice. FIG. 6Bdepicts a disc. The top surface of the disc would slide beneath theorifice along the bottom surface of the orifice plate support to openand close the orifice. The body surfaces have a high density refractorylining.

Hydraulic Actuators employ hydraulic pressure to drive an output memberand are used where high speed and large forces are required. The fluidused in hydraulic actuator is highly incompressible so that pressureapplied can be transmitted instantaneously to the member attached to it.In the slide activator, the hydraulic fluid drives a piston to move thevalve disc. Fluid may be supplied by local actuator or by a central oilsystem for entire system. A hand pump may be present if there is afailure of pressure supply. The system may have redundant components(e.g. solenoids) in case one fails.

Normal design speed for slide valve actuators may be full stroke in 5seconds using normal hydraulic circuit. Shutdown design speed for slidevalve actuators may be full stroke in 2 seconds using shutdown circuit.Dynamic response or speed of response for any step change may be in therange of 2% to 10% of full valve travel. Dead time T(d) the time betweenwhen a command is sent and the valve begins to move. Hysteresis is therange that the control signal may be varied before the valve changesdirection and relates to the time after an input signal step changeuntil the slide valve system will respond and is, for example, less than0.3 seconds. Step response after an input signal step change until theoutput has reached 63% of the final steady state value (T(63)) is, forexample, less than 0.4 seconds. Step response time after an input signalstep change until the output has reached, for example, 86.5% of thefinal steady state value (T(86)) is, for example, less than 0.5 seconds.

FIG. 9 depicts an electro-hydraulic slide valve actuator system with anindividual power source. A piston operator is directly connected to theslide valve. The electro-hydraulic power unit is a sealed system withits own internal hydraulic reservoir. The hydraulic pump is driven by anelectric motor. An accumulator in a hydraulic system provides a means ofstoring the incompressible fluids under pressure. The main accumulatorholds pressure for two full strokes and the reserve accumulator holdspressure for additional two strokes. Two pumps are present and one pumpis continuously running. The pumps can drive the valve themselves whenaccumulators are depleted, but slowly. The piston is moved using theservo valve, which directs hydraulic fluid to one side of the piston orthe other. A position transmitter may be provided to provide feedback tocompare against the position set point.

Sensor Data Processing

The system may include one or more computing devices or platforms forcollecting, storing, processing, and analyzing data from one or moresensors. FIG. 10A depicts an illustrative computing system that may beimplemented at one or more components, pieces of equipment, and/orplants. FIG. 10A-FIG. 10E (hereinafter collectively “FIG. 10”), show, byway of illustration, various components of the illustrative computingsystem in which aspects of the disclosure may be practiced. It is to beunderstood that other components may be used, and structural andfunctional modifications may be made, in one or more other embodimentswithout departing from the scope of the present disclosure. Moreover,various connections between elements are discussed in the followingdescription, and these connections are general and, unless specifiedotherwise, may be direct or indirect, wired or wireless, and/orcombination thereof, and that the specification is not intended to belimiting in this respect.

FIG. 10A depicts an illustrative operating environment in which variousaspects of the present disclosure may be implemented in accordance withexample embodiments. The computing system environment 1000 illustratedin FIG. 10A is only one example of a suitable computing environment andis not intended to suggest any limitation as to the scope of use orfunctionality contained in the disclosure. The computing systemenvironment 1000 may include various sensor, measurement, and datacapture systems, a data collection platform 1002, a data analysisplatform 1004, a control platform 1006, one or more networks, one ormore remote devices 1054, 1056, and/or one or more other elements. Thenumerous elements of the computing system environment of FIG. 10A may becommunicatively coupled through one or more networks. For example, thenumerous platforms, devices, sensors, and/or components of the computingsystem environment may be communicatively coupled through a privatenetwork 1008. The sensors be positioned on various components in theplant and may communicate wirelessly or wired with one or more platformsillustrated in FIG. 10A. The private network 1008 may include, in someexamples, a network firewall device to prevent unauthorized access tothe data and devices on the private network 1008. Alternatively oradditionally, the private network 1008 may be isolated from externalaccess through physical means, such as a hard-wired network with noexternal, direct access point. The data communicated on the privatenetwork 1008 may be optionally encrypted for further security. Dependingon the frequency of collection and transmission of sensor measurementsand other data to the data collection platform 1002, the private network1008 may experience large bandwidth usage and be technologicallydesigned and arranged to accommodate for such technological issues.Moreover, the computing system environment 1000 may also include apublic network 1010 that may be accessible to remote devices (e.g.,remote device 1054, remote device 1056). In some examples, a remotedevice may be located not in the proximity (e.g., more than one mileaway) of the various sensor, measurement, and data capture systemsillustrated in FIG. 10A. In other examples, the remote device may bephysically located inside a plant, but restricted from access to theprivate network 1008; in other words, the adjective “remote,” need notnecessarily require the device to be located at a great distance fromthe sensor systems and other components.

Although the computing system environment of FIG. 10A illustrateslogical block diagrams of numerous platforms and devices, the disclosureis not so limited. In particular, one or more of the logical boxes inFIG. 10 may be combined into a single logical box or the functionalityperformed by a single logical box may be divided across multipleexisting or new logical boxes. For example, aspects of the functionalityperformed by the data collection platform 1002 may be incorporated intoone or each of the sensor devices illustrated in FIG. 10A. As such, thedata collection may occur local to the sensor device, and the enhancedsensor system may communicate directly with one or more of the controlplatform 1006 and/or data analysis platform 1004. Such an embodiment iscontemplated by FIG. 10A. Moreover, in such an embodiment, the enhancedsensor system may measure values common to a sensor, but may also filterthe measurements such just those values that are statistically relevantor of-interest to the computing system environment are transmitted bythe enhanced sensor system. As a result, the enhanced sensor system mayinclude a processor (or other circuitry that enables execution ofcomputer instructions) and a memory to store those instructions and/orfiltered data values. The processor may be embodied as anapplication-specific integrated circuit (ASIC), FPGA, or other hardware-or software-based module for execution of instructions. In anotherexample, one or more sensors illustrated in FIG. 10A may be combinedinto an enhanced, multi-purpose sensor system. Such a combined sensorsystem may provide economies of scale with respect to hardwarecomponents such as processors, memories, communication interfaces, andothers.

In yet another example, the data collection platform 1002 and dataanalysis platform 1004 may reside on a single server computer anddepicted as a single, combined logical box on a system diagram.Moreover, a data store may be illustrated in FIG. 10A separate and apartfrom the data collection platform 1002 and data analysis platform 1004to store a large amount of values collected from sensors and othercomponents. The data store may be embodied in a database format and maybe made accessible to the public network 1010; meanwhile, the controlplatform 1006, data collection platform 1002, and data analysis platform1004 may be restricted to the private network 1008 and left inaccessibleto the public network 1010. As such, the data collected from a plant maybe shared with users (e.g., engineers, data scientists, others), acompany's employees, and even third parties (e.g., subscribers to thecompany's data feed) without compromising potential securityrequirements related to operation of a plant. The data store may beaccessible to one or more users and/or remote devices over the publicnetwork 1010.

Referring to FIG. 10A, process measurements from various sensor andmonitoring devices may be used to monitor conditions in, around, and onprocess equipment. Such sensors may include, but are not limited to,pressure sensors 1024, differential pressure sensors 1036, disc sensors1022, venturi 1038, other flow sensors 1030, temperature sensors 1012including thermal cameras 1020 and skin thermocouples, capacitancesensors 1034, weight sensors 1032, gas chromatographs 1014, moisturesensors 1016, ultrasonic sensors 1018, position sensors 1028, timingsensors, vibration sensors 1026, microphones, level sensors 1046, liquidlevel (hydraulic fluid) sensors, and other sensors used in the refiningand petrochemical industry. Further, process laboratory measurements maybe taken using gas chromatographs 1014, liquid chromatographs,distillation measurements, octane measurements, and other laboratorymeasurements.

In addition, sensors may include transmitters and/or deviation alarms.These sensors may be programmed to set off an alarm. For example, if anactuator fails, a sensor may automatically trigger an alarm. Othersensors may transmit signals to a processor or a hub that collects thedata and sends to a processor. For example, temperature and pressuremeasurements may be sent to a hub (e.g., data collection platform 1002).In one example, temperature sensors 1012 may include thermocouples,fiber optic temperature measurement, thermal cameras 1020, and/orinfrared cameras. Skin thermocouples may be placed directly on a wall ofa slide valve component such as the valve body, the discs, and the stem.Alternatively or additionally, skin thermocouples may be applied totubes or plates and thermal (infrared) cameras 1020 may be used todetect hot spots in all aspects of the equipment including bundles(tubes). A shielded (insulated) tube skin thermocouple assembly may beused to obtain accurate measurements. One example of a thermocouple maybe a removable Xtracto™ Pad. A thermocouple can be replaced without anyadditional welding. Clips and/or pads may be utilized for ease ofreplacement. One or more thermal or infrared cameras may be placed on oraround a slide valve.

In another example, a position sensor may detect a valve positionmagnetically or using a mechanical-limit switch. A position sensor maydetermine proximity. A position sensor may determine when a component ofthe system moves between a first position and a second position (e.g.,when the disc moves from an open to a closed position, or when thepiston moves from an extended to a retracted position). For example, apositional sensor can sense whether the disc is opening and closingcompletely.

FIG. 8 depicts an illustrative calibration for a slide valve actuator. Aposition sensor may determine a position of the slide valve actuator.The position sensor may measure 0% when the slide valve is in the fullyclosed position (valve orifice covered). The position sensor may measure100% when the slide valve is in the fully open position (valve orificeuncovered). System operational measurements also can be taken tocorrelate the system operation to the slide valve measurements.

Alternatively or additionally, pressure sensors, level sensors, andtemperature sensors may be used to take various data measurements of oneor more parts of a slide valve actuator. Pressure sensors may be used toverify solenoid operation. Pressure sensors may be placed on the pistonand accumulators. Temperature and level sensors may be placed on or inthe hydraulic reservoir and accumulators. Pressure sensors may be placedon or in discs, e.g., one for each side of piston. Measurements frompiston pressure sensors may be used to calculate output thrust value. Alow pressure setpoint may be calculated, which may, for example, beequivalent to the minimum pressure required to stroke the piston fromfull open to full closed one time, based on maximum travel. Timingsensors may be placed on or near the pistons, stems, and/or discs tomeasure the time it takes to open and close the disc over the orifice.Liquid level sensors may be placed to determine hydraulic fluid levelsfor hydraulic pistons.

In another example, strain sensors may test the strain on a part. Straingauges may be applied on or in metal surfaces to measure strain, forexample in the disc or stem. A strain gauge may be more sensitive in aparticular direction (e.g., a strain gauge may be more sensitive in ahorizontal direction than a vertical direction, or may be more sensitivein a vertical direction than a horizontal direction). A strain gauge mayinclude an electrical conductor (e.g., foil, semiconductor,nanoparticle) that, when subjected to a strain (e.g., compression orstretching) in a particular direction, may increase or decrease inelectrical conductivity. The gauge's resistance will experience acorresponding change (increased or decreased electrical conductivity),which allows for an amount of induced stress on the strain gauge to bedetermined when a voltage is applied to the gauge.

Sensor Data Collection

Sensor data, process measurements, and/or calculations made using thesensor data or process measurements may be used to monitor and/orimprove the performance of the equipment and parts making up theequipment, as discussed in further detail below. For example, sensordata may be used to detect that a desirable or an undesirable chemicalreaction is taking place within a particular piece of equipment, and oneor more actions may be taken to encourage or inhibit the chemicalreaction. Chemical sensors may be used to detect the presence of one ormore chemicals, such as corrosive species, oxygen, hydrogen, and/orwater (moisture). In another example, equipment information, such aswear, efficiency, production, state, or other condition information, maybe gathered and determined based on sensor data. Corrective action maybe taken based on determining this equipment information. For example,if the equipment is showing signs of wear or failure, corrective actionsmay be taken, such as taking an inventory of parts to ensure replacementparts are available, ordering replacement parts, and/or calling inrepair personnel to the site. Certain parts of equipment may be replacedimmediately. Other parts may be safe to use, but a monitoring schedulemay be adjusted. Alternatively or additionally, one or more inputs orcontrols relating to a process may be adjusted as part of the correctiveaction. These and other details about the equipment, sensors, processingof sensor data, and actions taken based on sensor data are described infurther detail below.

Monitoring the slide valves and the processes using slide valvesincludes collecting data that can be correlated and used to predictbehavior or problems in different slide valves used in the same plant orin other plants and/or processes. Process changes or operatingconditions may be able to be altered to preserve the equipment until thenext scheduled maintenance period.

Systems Facilitating Sensor Data Collection

Sensor data may be collected by a data collection platform 1002. Thesensors may interface with the data collection platform 1002 via wiredor wireless transmissions. The data collection platform 1002 maycontinuously or periodically (e.g., every second, every minute, everyhour, every day, once a week, once a month, etc.) transmit collectedsensor data to a data analysis platform 1004, which may be nearby orremote from the data collection platform 1002.

Sensor data (e.g., temperature data) may be collected continuously or atperiodic intervals (e.g., every second, every five seconds, every tenseconds, every minute, every five minutes, every ten minutes, everyhour, every two hours, every five hours, every twelve hours, every day,every other day, every week, every other week, every month, every othermonth, every six months, every year, or another interval). Data may becollected at different spots at different intervals. For example, dataat a known hot spot may be collected at a first interval, and data at aspot that is not a known hot spot may be collected at a second interval.

The computing system environment of FIG. 10A includes logical blockdiagrams of numerous platforms and devices that are further elaboratedupon in FIG. 10B, FIG. 10C, FIG. 10D, and FIG. 10E. FIG. 10B is anillustrative data collection platform 1002. FIG. 10C is an illustrativedata analysis platform 1004. FIG. 10D is an illustrative controlplatform 1006. FIG. 10E is an illustrative remote device 1054. Theseplatforms and devices of FIG. 10 include one or more processing units(e.g., processors) to implement the methods and functions of certainaspects of the present disclosure in accordance with the exampleembodiments. The processors may include general-purpose microprocessorsand/or special-purpose processors designed for particular computingsystem environments or configurations. For example, the processors mayexecute computer-executable instructions in the form of software and/orfirmware stored in the memory of the platform or device. Examples ofcomputing systems, environments, and/or configurations that may besuitable for use with the disclosed embodiments include, but are notlimited to, personal computers (PCs), server computers, hand-held orlaptop devices, smart phones, multiprocessor systems,microprocessor-based systems, programmable consumer electronics, networkPCs, minicomputers, mainframe computers, distributed computingenvironments that include any of the above systems or devices, and thelike.

In addition, the platform and/or devices in FIG. 10 may include one ormore memories include any of a variety of computer readable media.Computer readable media may be any available media that may be accessedby the data collection platform 1002, may be non-transitory, and mayinclude volatile and nonvolatile, removable and non-removable mediaimplemented in any method or technology for storage of information suchas computer-readable instructions, object code, data structures,database records, program modules, or other data. Examples of computerreadable media may include random access memory (RAM), read only memory(ROM), electronically erasable programmable read only memory (EEPROM),flash memory or other memory technology, compact disk read-only memory(CD-ROM), digital versatile disks (DVD) or other optical disk storage,magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices, or any other medium that can be used to storethe desired information and that can be accessed by the data collectionplatform 1002. The memories in the platform and/or devices may furtherstore modules that may include compiled software code that causes theplatform, device, and/or overall system to operate in a technologicallyimproved manner as disclosed herein. For example, the memories may storesoftware used by a computing platform, such as operating system,application programs, and/or associated database.

Furthermore, the platform and/or devices in FIG. 10 may include one ormore communication interfaces including, but are not limited to, amicrophone, keypad, touch screen, and/or stylus through which a user ofa computer (e.g., a remote device) may provide input, and may alsoinclude a speaker for providing audio output and a video display devicefor providing textual, audiovisual and/or graphical output. Thecommunication interfaces may include a network controller forelectronically communicating (e.g., wirelessly or wired) over a publicnetwork 1010 or private network 1008 with one or more other componentson the network. The network controller may include electronic hardwarefor communicating over network protocols, including TCP/IP, UDP,Ethernet, and other protocols.

In some examples, one or more sensor devices in FIG. 10A may be enhancedby incorporating functionality that may otherwise be found in a datacollection platform 1002. These enhanced sensor system may providefurther filtering of the measurements and readings collected from theirsensor devices. For example, with some of the enhanced sensor systems inthe operating environment illustrated in FIG. 10A, an increased amountof processing may occur at the sensor so as to reduce the amount of dataneeding to be transferred over a private network 1008 in real-time to acomputing platform. The enhanced sensor system may filter at the sensoritself the measured/collected/captured data and only particular,filtered data may be transmitted to the data collection platform 1002for storage and/or analysis.

Referring to FIG. 10B, in one example, a data collection platform 1002may include one or more processors 1060, one or more memories 1062, andcommunication interfaces 1068. The memory 1062 may include a database1064 for storing data records of various values collected from one ormore sources. In addition, a data collection module 1066 may be storedin the memory 1062 and assist the processor 1060 in the data collectionplatform 1002 in communicating with, via the communications interface1068, one or more sensor, measurement, and data capture systems, andprocessing the data received from these sources. In some embodiments,the data collection module 1066 may include computer-executableinstructions that, when executed by the processor 1060, cause the datacollection platform 1002 to perform one or more of the steps disclosedherein. In other embodiments, the data collection module 1066 may be ahybrid of software-based and/or hardware-based instructions to performone or more of the steps disclosed herein. In some examples, the datacollection module 1066 may assist an enhanced sensor system with furtherfiltering the measurements and readings collected from the sensordevices. Although the elements of FIG. 10B are illustrated as logicalblock diagrams, the disclosure is not so limited. In particular, one ormore of the logical boxes in FIG. 10B may be combined into a singlelogical box or the functionality performed by a single logical box maybe divided across multiple existing or new logical boxes. Moreover, somelogical boxes that are visually presented as being inside of anotherlogical box may be moved such that they are partially or completelyresiding outside of that logical box. For example, while the database1064 in FIG. 10B is illustrated as being stored inside one or morememories 1062 in the data collection platform 1002, FIG. 10Bcontemplates that the database 1064 may be stored in a standalone datastore communicatively coupled to the data collection module 1066 andprocessor 1060 of the data collection platform 1002 via thecommunications interface 1068 of the data collection platform 1002.

In addition, the data collection module 1066 may assist the processor1060 in the data collection platform 1002 in communicating with, via thecommunications interface 1068, and processing data received from othersources, such as data feeds from third-party servers and manual entry atthe field site from a dashboard graphical user interface. For example, athird-party server may provide contemporaneous weather data to the datacollection module. Some elements of chemical and petrochemical/refineryplants may be exposed to the outside and thus may be exposed to variousenvironmental stresses. Such stresses may be weather related such astemperature extremes (hot and cold), high wind conditions, andprecipitation conditions such as snow, ice, and rain. Otherenvironmental conditions may be pollution particulates such as dust andpollen, or salt if located near an ocean, for example. Such stresses canaffect the performance and lifetime of equipment in the plants.Different locations may have different environmental stresses. Forexample, a refinery in Texas will have different stresses than achemical plant in Montana. In another example, data manually enteredfrom a dashboard graphical user interface (or other means) may becollected and saved into memory by the data collection module.Production rates may be entered and saved in memory. Tracking productionrates may indicate issues with flows. For example, as fouling occurs,the production rate may fall if a specific outlet temperature can nolonger be achieved at the targeted capacity and capacity has to bereduced to maintain the targeted outlet temperature.

Referring to FIG. 10C, in one example, a data analysis platform 1004 mayinclude one or more processors 1070, one or more memories 1072, andcommunication interfaces 1082. The memory 1072 may include a database1074 for storing data records of various values collected from one ormore sources. Alternatively or additionally, the database 1074 may bethe same database as that depicted in FIG. 10B and the data analysisplatform 1004 may communicatively couple with the database 1074 via thecommunication interface of the data analysis platform 1004. At least oneadvantage of sharing a database between the two platforms is the reducedmemory requirements due to not duplicating of the same or similar data.In addition, a data analysis module 1076 may be stored in the memory1072 and assist the processor 1070 in the data analysis platform 1004 inprocessing and analyzing the data values stored in the database 1074. Insome embodiments, the data analysis module 1076 may includecomputer-executable instructions that, when executed by the processor1070, cause the data analysis platform 1004 to perform one or more ofthe steps disclosed herein. In other embodiments, the data analysismodule 1076 may be a hybrid of software-based and/or hardware-basedinstructions to perform one or more of the steps disclosed herein. Insome embodiments, the data analysis module 1076 may perform statisticalanalysis, predictive analytics, and/or machine learning on the datavalues in the database 1074 to generate predictions and models. Forexample, the data analysis platform 1004 may analyze sensor data todetect new hot spots and/or to monitor existing hot spots (e.g., todetermine if an existing hot spot is growing, maintaining the same size,or shrinking) in the equipment of a plant. The data analysis platform1004 may compare temperature data from different dates to determine ifchanges are occurring. Such comparisons may be made on a monthly,weekly, daily, hourly, real-time, or some other basis.

Referring to FIG. 10C, the recommendation module 1078 in the dataanalysis platform 1004 may coordinate with the data analysis module 1076to generate recommendations for adjusting one or more parameters for theoperation of the plant environment depicted in FIG. 10A. In someembodiments, the recommendation module 1078 may communicate therecommendation to the command module 1080, which may generate commandcodes that may be transmitted, via the communications interface, tocause adjustments or halting/starting of one or more operations in theplant environment. The command codes may be transmitted to a controlplatform 1006 for processing and/or execution. In one or moreembodiments, the command codes may be directly communicated, eitherwirelessly or in a wired fashion, to physical components at the plantsuch that the physical components include an interface to receive thecommands and execute on them.

Although the elements of FIG. 10C are illustrated as logical blockdiagrams, the disclosure is not so limited. In particular, one or moreof the logical boxes in FIG. 10C may be combined into a single logicalbox or the functionality performed by a single logical box may bedivided across multiple existing or new logical boxes. Moreover, somelogical boxes that are visually presented as being inside of anotherlogical box may be moved such that they are partially or completelyresiding outside of that logical box. For example, while the database isvisually depicted in FIG. 10C as being stored inside one or morememories in the data analysis platform 1004, FIG. 10C contemplates thatthe database may be stored in a standalone data store communicativelycoupled to the data analysis module and processor of the data analysisplatform 1004 via the communications interface of the data analysisplatform 1004. Furthermore, the databases from multiple plant locationsmay be shared and holistically analyzed to identify one or more trendsand/or patterns in the operation and behavior of the plant and/or plantequipment. In such a crowdsourcing-type example, a distributed databasearrangement may be provided where a logical database may simply serve asan interface through which multiple, separate databases may be accessed.As such, a computer with predictive analytic capabilities may access thelogical database to analyze, recommend, and/or predict the behavior ofone or more aspects of plants and/or equipment. In another example, thedata values from a database from each plant may be combined and/orcollated into a single database where predictive analytic engines mayperform calculations and prediction models.

Referring to FIG. 10D, in one example, a control platform 1006 mayinclude one or more processors 1084, one or more memories 1086, andcommunication interfaces 1092. The memory 1086 may include a database1088 for storing data records of various values transmitted from a userinterface, computing device, or other platform. The values may includeparameter values for particular equipment at the plant. For example,some illustrative equipment at the plant that may be configured and/orcontrolled by the control platform 1006 include, but is not limited to,a feed switcher, sprayer, one or more valves, one or more pumps, one ormore gates, and/or one or more drains. In addition, a control module1090 may be stored in the memory and assist the processor in the controlplatform 1006 in receiving, storing, and transmitting the data valuesstored in the database. In some embodiments, the control module 1090 mayinclude computer-executable instructions that, when executed by theprocessor 1084, cause the control platform 1006 to perform one or moreof the steps disclosed herein. In other embodiments, the control modulemay be a hybrid of software-based and/or hardware-based instructions toperform one or more of the steps disclosed herein.

In a plant environment such as illustrated in FIG. 10A, if sensor datais outside of a safe range, this may be cause for immediate danger. Assuch, there is a real-time component to the system such that the systemprocesses and responds in a timely manner. Although in some embodiments,data could be collected and leisurely analyzed over a lengthy period ofmonths, numerous embodiments contemplate a real-time or near real-timeresponsiveness in analyzing and generating alerts, such as thosegenerated by the alert module in FIG. 10E.

Referring to FIG. 10E, in one example, a remote device 1054 may includeone or more processors 1093, one or more memories 1094, andcommunication interfaces 1099. The memory 1094 may include a database1095 for storing data records of various values entered by a user orreceived through the communications interface. In addition, an alertmodule 1096, command module 1097, and/or dashboard module 1098 may bestored in the memory 1094 and assist the processor 1093 in the remotedevice 1054 in processing and analyzing the data values stored in thedatabase. In some embodiments, the aforementioned modules may includecomputer-executable instructions that, when executed by the processor,cause the remote device 1054 to perform one or more of the stepsdisclosed herein. In other embodiments, the aforementioned modules maybe a hybrid of software-based and/or hardware-based instructions toperform one or more of the steps disclosed herein. In some embodiments,the aforementioned modules may generate alerts based on values receivedthrough the communications interface. The values may indicate adangerous condition or even merely a warning condition due to odd sensorreadings. The command module 1097 in the remote device 1054 may generatea command that when transmitted through the communications interface tothe platforms at the plant, causes adjusting of one or more parameteroperations of the plant environment depicted in FIG. 10A. In someembodiments, the dashboard module 1098 may display a graphical userinterface to a user of the remote device 1054 to enable the user toenter desired parameters and/or commands. These parameters/commands maybe transmitted to the command module 1097 to generate the appropriateresulting command codes that may be then transmitted, via thecommunications interface, to cause adjustments or halting/starting ofone or more operations in the plant environment. The command codes maybe transmitted to a control platform 1006 for processing and/orexecution. In one or more embodiments, the command codes may be directlycommunicated, either wirelessly or in a wired fashion, to physicalcomponents at the plant such that the physical components include aninterface to receive the commands and execute on them.

Although FIG. 10E is not so limited, in some embodiments the remotedevice 1054 may include a desktop computer, a smartphone, a wirelessdevice, a tablet computer, a laptop computer, and/or the like. Theremote device 1054 may be physically located locally or remotely, andmay be connected by one of communications links to the public network1010 that is linked via a communications link to the private network1008. The network used to connect the remote device 1054 may be anysuitable computer network including the Internet, an intranet, awide-area network (WAN), a local-area network (LAN), a wireless network,a digital subscriber line (DSL) network, a frame relay network, anasynchronous transfer mode (ATM) network, a virtual private network 1008(VPN), or any combination of any of the same. Communications links maybe any communications links suitable for communicating betweenworkstations and server, such as network links, dial-up links, wirelesslinks, hard-wired links, as well as network types developed in thefuture, and the like. Various protocols such as transmission controlprotocol/Internet protocol (TCP/IP), Ethernet, file transfer protocol(FTP), hypertext transfer protocol (HTTP) and the like may be used, andthe system can be operated in a client-server configuration to permit auser to retrieve web pages from a web-based server. Any of variousconventional web browsers can be used to display and manipulate data onweb pages.

Although the elements of FIG. 10E are illustrated as logical blockdiagrams, the disclosure is not so limited. In particular, one or moreof the logical boxes in FIG. 10E may be combined into a single logicalbox or the functionality performed by a single logical box may bedivided across multiple existing or new logical boxes. Moreover, somelogical boxes that are visually presented as being inside of anotherlogical box may be moved such that they are partially or completelyresiding outside of that logical box. For example, while the database isvisually depicted in FIG. 10E as being stored inside one or morememories in the remote device 1054, FIG. 10E contemplates that thedatabase may be stored in a standalone data store communicativelycoupled, via the communications interface, to the modules stored at theremote device 1054 and processor of the remote device 1054.

Referring to FIG. 10, in some examples, the performance of operation ina plant may be improved by using a cloud computing infrastructure andassociated methods, as described in US Patent Application PublicationNo. US2016/0260041, which was published Sep. 8, 2016, and which isherein incorporated by reference in its entirety. The methods mayinclude, in some examples, obtaining plant operation information fromthe plant and/or generating a plant process model using the plantoperation information. The method may include receiving plant operationinformation over the Internet, or other computer network (includingthose described herein) and automatically generating a plant processmodel using the plant operation information. These plant process modelsmay be configured and used to monitor, predict, and/or optimizeperformance of individual process units, operating blocks and/orcomplete processing systems. Routine and frequent analysis of predictedversus actual performance may further allow early identification ofoperational discrepancies, which may be acted upon to optimize impact.

The aforementioned cloud computing infrastructure may use a datacollection platform 1002 associated with a plant to capture data, e.g.,sensor measurements, which may be automatically sent to the cloudinfrastructure, which may be remotely located, where it may be reviewedto, for example, eliminate errors and biases, and used to calculate andreport performance results. The data collection platform 1002 mayinclude an optimization unit that acquires data from a customer site,other site, and/or plant (e.g., sensors and other data collectors at aplant) on a recurring basis. For cleansing, the data may be analyzed forcompleteness and corrected for gross errors by the optimization unit.The data may also be corrected for measurement issues (e.g., an accuracyproblem for establishing a simulation steady state) and overall massbalance closure to generate a duplicate set of reconciled plant data.The corrected data may be used as an input to a simulation process, inwhich the process model is tuned to ensure that the simulation processmatches the reconciled plant data. An output of the reconciled plantdata may be used to generate predicted data using a collection ofvirtual process model objects as a unit of process design.

The performance of the plant and/or individual process units of theplant is/are compared to the performance predicted by one or moreprocess models to identify any operating differences or gaps.Furthermore, the process models and collected data (e.g., plantoperation information) may be used to run optimization routines thatconverge on an optimal plant operation for a given values of, e.g.,feed, products, and/or prices. A routine may be understood to refer to asequence of computer programs or instructions for performing aparticular task.

The data analysis platform 1004 may include an analysis unit thatdetermines operating status, based on at least one of a kinetic model, aparametric model, an analytical tool, and a related knowledge and bestpractice standard. The analysis unit may receive historical and/orcurrent performance data from one or a plurality of plants toproactively predict future actions to be performed. To predict variouslimits of a particular process and stay within the acceptable range oflimits, the analysis unit may determine target operational parameters ofa final product based on actual current and/or historical operationalparameters. This evaluation by the analysis unit may be used toproactively predict future actions to be performed. In another example,the analysis unit may establish a boundary or threshold of an operatingparameter of the plant based on at least one of an existing limit and anoperation condition. In yet another example, the analysis unit mayestablish a relationship between at least two operational parametersrelated to a specific process for the operation of the plant. Finally inyet another example, one or more of the aforementioned examples may beperformed with or without a combination of the other examples.

The plant process model predicts plant performance that is expectedbased upon the plant operation information. The plant process modelresults can be used to monitor the health of the plant and to determinewhether any upset or poor measurement occurred. The plant process modelis desirably generated by an iterative process that models at variousplant constraints to determine the desired plant process model.

Using a web-based system for implementing the method of this disclosureprovides many benefits, such as improved plant economic performance dueto an increased ability by plant operators to identify and captureeconomic opportunities, a sustained ability to bridge plant performancegaps, and an increased ability to leverage personnel expertise andimprove training and development. Some of the methods disclosed hereinallow for automated daily evaluation of process performance, therebyincreasing the frequency of performance review with less time and effortrequired from plant operations staff.

Further, the analytics unit may be partially or fully automated. In oneembodiment, the system is performed by a computer system, such as athird-party computer system, remote from the plant and/or the plantplanning center. The system may receive signals and parameters via thecommunication network, and displays in real time related performanceinformation on an interactive display device accessible to an operatoror user. The web-based platform allows all users to work with the sameinformation, thereby creating a collaborative environment for sharingbest practices or for troubleshooting. The method further provides moreaccurate prediction and optimization results due to fully configuredmodels. Routine automated evaluation of plant planning and operationmodels allows timely plant model tuning to reduce or eliminate gapsbetween plant models and the actual plant performance. Implementing theaforementioned methods using the web-based platform also allows formonitoring and updating multiple sites, thereby better enabling facilityplanners to propose realistic optimal targets.

FIGS. 11A-11B depict illustrative system flow diagrams in accordancewith one or more embodiments described herein. As shown in FIG. 11A, instep 201, data collection platform 1002 may collect sensor data. In step202, data collection platform 1002 may transmit sensor data to dataanalysis platform 1004. In step 203, data analysis platform 1004 mayanalyze data. In step 204, data analysis platform 1004 may send an alertto remote device 1054 and/or remote device 1056.

As shown in FIG. 11B, in step 205, data analysis platform 1004 mayreceive a command from remote device 1054 and/or remote device 1056. Insome embodiments, the control platform 1006 may receive the command fromremote device 1054 and/or remote device 1056. In step 206, data analysisplatform 1004 may send a command to control platform 1006. In someembodiments, the command may be similar to the command received fromremote device 1054 and/or remote device 1056. In some embodiments, dataanalysis platform 1004 may perform additional analysis based on thereceived command from remote device 1054 and/or remote device 1056before sending a command to control platform 1006. In step 207, controlplatform 1006 may take corrective action. The corrective action may bebased on the command received from data analysis platform 1004, remotedevice 1054, and/or remote device 1056. The corrective action may berelated to one or more pieces of equipment (e.g., slide valve)associated with sensors that collected the sensor data in step 201.

FIG. 14 depicts an illustrative flow diagram in accordance with one ormore embodiments described herein. The flow may be performed by one ormore devices, which may be interconnected via one or more networks.

First, the one or more devices may collect 1402 sensor data. The sensordata may be from one or more sensors attached to one or more pieces ofequipment (e.g., a slide valve) in a plant. The sensor data may belocally collected and processed and/or may be locally collected andtransmitted for processing.

After the sensor data is collected, the one or more devices may process1404 the sensor data. The one or more devices may compare the data topast data from the one or more pieces of equipment, other pieces ofequipment at a same plant, one or more pieces of equipment at adifferent plant, manufacturer recommendations or specifications, or thelike.

After the sensor data is processed, the one or more devices maydetermine 1406 one or more recommendations based on the sensor data. Theone or more recommendations may include recommendations of one or moreactions to take based on the sensor data.

The one or more devices may send 1408 one or more alerts, which mayinclude the determined recommendation. The one or more alerts mayinclude information about the sensor data, about other data, or thelike.

The one or more devices may receive 1410 a command to take an action(e.g., the recommended action, an action other than the recommendedaction, or no action). After receiving the command, the one or moredevices may take 1412 the action. The action may, in some embodiments,include one or more corrective actions, which may cause one or morechanges in the operation of the one or more pieces of equipment.

FIG. 12 depicts an illustrative graphical user interface 1200 of anapplication that may be used for providing information received from oneor more sensors or determined based on analyzing information receivedfrom one or more sensors, according to one or more embodiments describedherein. The graphical user interface may be displayed as part of asmartphone application (e.g., running on a remote device, such as remotedevice 1 or remote device 2), a desktop application, a web application(e.g., that runs in a web browser), a web site, an application runningon a plant computer, or the like.

The graphical user interface 1200 may include one or more visualrepresentations of data (e.g., chart, graph, etc.) that showsinformation about a plant, a particular piece of equipment in a plant,or a process performed by a plant or a particular piece or combinationof equipment in the plant. For example, a graph may show informationabout an operating condition, an efficiency, a production level, or thelike. The graphical user interface 1200 may include a description of theequipment, the combination of equipment, or the plant to which thevisual display of information pertains.

The graphical user interface 1200 may display the information for aparticular time or period of time (e.g., the last five minutes, the lastten minutes, the last hour, the last two hours, the last 12 hours, thelast 24 hours, etc.). The graphical user interface may be adjustable toshow different ranges of time, automatically or based on user input.

The graphical user interface 1200 may include one or more buttons thatallow a user to take one or more actions. For example, the graphicaluser interface may include a button (e.g., an “Actions” button) that,when pressed, shows one or more actions available to the user. Thegraphical user interface may include a button (e.g., a “Change View”button) that, when pressed, changes one or more views of one or moreelements of the graphical user interface. The graphical user interfacemay include a button (e.g., a “Settings” button) that, when pressed,shows one or more settings of the application of which the graphicaluser interface is a part. The graphical user interface may include abutton (e.g., a “Refresh Data” button) that, when pressed, refreshesdata displayed by the graphical user interface. In some aspects, datadisplayed by the graphical user interface may be refreshed in real time,according to a preset schedule (e.g., every five seconds, every tenseconds, every minute, etc.), and/or in response to a refresh requestreceived from a user. The graphical user interface may include a button(e.g., a “Send Data” button) that, when pressed, allows a user to senddata to one or more other devices. For example, the user may be able tosend data via email, SMS, text message, iMessage, FTP, cloud sharing,Airdrop, or via some other method. The user may be able to select one ormore pieces of data, graphics, charts, graphs, elements of the display,or the like to share or send. The graphical user interface may include abutton (e.g., an “Analyze Data” button) that, when pressed, causes oneor more data analysis functions to be performed. In some aspects, theuser may provide additional input about the desired data analysis, suchas desired input, desired output, desired granularity, desired time tocomplete the data analysis, desired time of input data, or the like.

FIG. 13 depicts an illustrative graphical user interface 1300 of anapplication that may be used for providing alerts and/or receiving orgenerating commands for taking corrective action, in accordance with oneor more embodiments described herein. The graphical user interface 1300may include an alert with information about a current state of a pieceof equipment, a problem being experienced by a piece of equipment, aproblem with a plant, or the like. For example, the graphical userinterface 1300 may include one or more alerts, such as an alert that aslide valve is stuck open, that a new hot spot has been detected, thatan existing hot spot is growing, or another alert.

The graphical user interface 1300 may include one or more buttons that,when pressed, cause one or more actions to be taken. For example, thegraphical user interface 1300 may include a button that, when pressed,causes a slide valve to attempt to open or close. In another example,the graphical user interface 1300 may include a button that, whenpressed, sends an alert to a contact (e.g., via a remote device), thealert including information similar to the information included in thealert provided via the graphical user interface. In a further example,the graphical user interface 1300 may include a button that, whenpressed, shows one or more other actions that may be taken (e.g.,additional corrective actions, such as adjust a hydraulic pressure,adjust a temperature, adjust a flow rate, or the like).

Early Prediction and Detection of Slide Valve Sticking

One or more sensors may be used in conjunction with one or more systemcomponents discussed herein to predict and detect slide valve sticking.Slide valve sticking may be indicative of a current or futuremaintenance need. Early detection may enable preventative treatment thatmight be able to slow or stop deterioration in equipment condition,thereby prolonging equipment life, extending production operating time,or providing other benefits.

One method of determining or predicting slide valve sticking is bymeasuring the time for a slide valve disc or piston to move from a firstposition to a second position. This time measurement may be monitored todetermine if problems are developing. For example, a developing problemmay be an agglomeration or a buildup of catalyst on the disc or guides,which may cause friction, slowing the time the disc takes to open orshut. Catalyst can be similar to sand or rocks, in that buildup of thecatalyst between the moving parts of the slide activator may cause thedisc to not slide cleanly and or not close or open completely. Thecatalyst can also affect the guides by slowing down the sliding of thedisc in the guide.

Using one or more sensors, the system can measure the time (T). Forexample, the data collection platform 1002 may receive, from a positionsensor, information indicating a position of an actuator, valve cover,or other component of a slide valve. The data collection platform 1002may correlate sensor information with other data, such as timeinformation. Specifically, for example, the data collection platform1002 may correlate a start time and a stop time with data received froma position sensor indicating movement of an actuator, valve cover, orother component of the slide valve. This information may be collected asmetadata corresponding to the sensor data.

A thermal gun may be used to measure slide valve temperatures.Alternatively or additionally, a shielded, tube skin thermocoupleassembly may provide a complete temperature profile. Alternatively oradditionally, one or more skin thermocouples may be connected to one ormore locations on the body or shell of the slide valve.

Alternatively or additionally, fiber optic temperature measurements maybe taken. Fiber optic cable can be attached to the line or vessel toprovide a complete profile of temperatures.

Tomography may be used to image the slide valve by sections orsectioning, through the use of any kind of a penetrating wave, such asinfrared. One or more thermal cameras may be used (e.g., mounted in oneor more fixed locations around a slide valve, attached to a robot thatmoves around a slide valve, carried by a plant worker) to regularlycapture thermal images of a slide valve. The thermal cameras may bemounted in a configuration such that a combination of images from thethermal cameras allow for viewing all exterior portions of a slidevalve. Alternatively or additionally, thermal cameras may be mounted sothat less than all exterior portions of a slide valve are visible in thethermal images (e.g., thermal imaging might only be taken of certainareas of the slide valve body). One or more cameras may capture one ormore images of the slide valve, which may, in some embodiments, allowfor convenient comparison of a thermal image with one or more locationson the slide valve. (X-Ray and Tracer Studies sometimes also used fortroubleshooting)

Sensor data may be collected continuously or at periodic intervals(e.g., every second, every five seconds, every ten seconds, everyminute, every five minutes, every ten minutes, every hour, every twohours, every five hours, every twelve hours, every day, every other day,every week, every other week, every month, every other month, every sixmonths, every year, or another interval). Data may be collected atdifferent locations at different intervals. For example, data at a firstlocation on the slide valve may be collected at a first interval, anddata at a second location on the slide valve may be collected at asecond interval. Alternatively or additionally, sensor data may becollected based on a particular event occurrence. For example, a thermalcycle event may trigger collection of sensor data from one or moresensors.

Sensor data may be collected by a data collection platform 1002. Thesensors may interface with the data collection platform 1002 via wiredor wireless transmissions. The data collection platform 1002 maycontinuously or periodically (e.g., every second, every minute, everyhour, every day, once a week, once a month, etc.) transmit collectedsensor data to a data analysis platform 1004, which may be nearby orremote from the data collection platform 1002.

The data analysis platform 1004 may analyze sensor data to detectpotential slide valve sticking and/or to monitor existing slide valvesticking. Slide valve operation data from different dates may becompared to determine if changes are occurring. Such comparisons may bemade on a monthly, weekly, daily, hourly, or some other basis.

For example, the data analysis platform 1004 may determine a particular(e.g., current, most recent) amount of time (ΔT) (e.g., using the starttime and stop time) that it takes for the slide valve to perform anoperation (e.g., valve moving from open to closed position, based on theposition sensor data). The data analysis platform 1004 may compare theparticular (e.g., current, most recent) ΔT to historical data for thesystem, component, or slide valve. For example, the historical data mayinclude the average ΔT for this system, the previous five, ten, fifteen,or some other number of ΔTs for this system. In another example, thedata analysis platform 1004 may compare the current ΔT to another slidevalve within the system, another slide valve at another plant or systemof a similar age, in a similar environment, performing a similarprocess, or the like. The data analysis platform 1004 may compare thecurrent ΔT to a manufacturer standard ΔT. The data analysis platform1004 may determine if the current ΔT differs from one or more other ΔTsby more than a preset amount or threshold (e.g., 5%, 10%, etc.).

In some embodiments, if it is difficult to move the discs, the pressurecan adversely affect the pistons and the actuator. Sensors, such aspressure and temperature sensors, may be placed on or in the piston. Forexample, a pressure sensor may measure the hydraulic pressure.

In some embodiments, the data analysis platform 1004 may determine,based on comparing the received sensor data (e.g., pressure sensor data,temperature sensor data, position sensor data, hydraulic-fluid levelsensor data) with other sensor data (e.g., historical sensor data,sensor data from other locations on the slide valve, sensor data fromother slide valves in the plant, sensor data from other slide valves inother plants, manufacturer-recommended sensor data, or the like),whether the sensor data for a particular slide valve is indicative of acurrent or developing problem. For example, a higher hydraulic pressuremay, in some instances, prevent the discs from sticking. In anotherexample, position sensors may measure the distance a piston moves froman extended to a retracted position, and may be monitored to see if theposition changes over time. In a further example, a hydraulic-fluidlevel sensor may be included to ensure there is sufficient hydraulicfluid in the piston.

In some embodiments, data from the sensors may be correlated withweather data at the plant. For example, if a rainstorm is currentlyhappening at the plant, the surface temperature, operating temperature,another temperature, and/or a pressure of the slide valve might drop. Inanother example, if a drought and heat wave are currently happening atthe plant, the surface temperature, operating temperature, anothertemperature, and/or a pressure of the slide valve might increase. Thedata analysis platform 1004 may determine, based on the correlation ofthe weather conditions to the changes in temperature data, that thechanges in temperature and/or pressure of the slide valve are due toweather conditions, and not, e.g., due to another problem that may beindicative of slide valve sticking.

In some embodiments, data analysis platform 1004 may determine, based onmonitoring data from one or more slide valves at one or more differentplants, if certain weather conditions and/or other operating conditionsare correlated with development of slide valve sticking.

In some embodiments, data from different types of sensors may becross-checked to confirm conclusions drawn from that data, to determinedata reliability, and the like. For example, temperature readings fromskin thermocouples may be compared to temperature readings from athermal imaging camera, thermal topography may be compared tophotographs, or the like.

In some aspects, data analysis platform 1004 may use additional datafrom the slide valve or from other equipment connected to the slidevalve (e.g., in the same plant, in a plant upstream of the plant, etc.)to determine additional information about the slide valve sticking. Forexample, if a potentially sticking valve being monitored maintains aconsistent ΔT or ΔT increases at a first rate when a first operatingcondition exists, and the potentially sticking valve maintains aconsistent ΔT or ΔT increases at a second rate when a second operatingcondition exists, the data analysis platform 1004 may determine such acorrelation by comparing the slide valve sensor data to other data. Oneor more examples of an operating condition may include, e.g., the plantis operated at a particular efficiency, a particular amount of feed isused, a particular operating temperature of a piece of equipmentupstream of the slide valve is maintained, a particular amount ofcatalyst is used, a particular temperature of catalyst is used, weatherconditions, and the like. In some aspects, a particular operatingcondition or combination of operating conditions may be determined to bemore likely to cause development of sticking valves or worsening,stability, or stabilization of potentially sticking valves.

In some aspects, data analysis platform 1004 may determine if a slidevalve sticking is approaching a known damage or failure condition. Forexample, if a slide valve is designed to open within a particular ΔT,and the current ΔT is within a range or threshold of exceeding theparticular ΔT, data analysis platform 1004 may determine that the slidevalve sticking may soon become severe enough to be classified asequipment failure (e.g., the valve may get stuck). Data analysisplatform 1004 may use historical data from the slide valve, data fromother slide valves at the plant, data from other plants, data from amanufacturer, specification data, or other data to determine how apotentially sticking valve might develop, stabilize, cause failure, orthe like.

In some embodiments, data analysis platform 1004 may determine one ormore failure modes in which to classify slide valve sticking. Forexample, slide valve sticking may occur in more than one way (e.g.,different parts of the slide valve may fail or erode, which eachindependently or in different combinations might cause sticking), andmight be detectable based on one or more data indicators from one ormore different sensor types. Furthermore, the different failure modesmay be associated with different corrective measures. For example, afirst failure mode might be a result of a first problem, might bedetectable by a first type of sensor data, and might be correctable by afirst action, while a second failure mode might be a result of a secondproblem, might be detectable by a second type of sensor data, and mightbe correctable by a second action.

Similarly, in some embodiments, (e.g., if the data analysis platform1004 determines a correlation between one or more operating conditionsand a potential problem, such as a higher likelihood to develop new orworsen existing sticking), if the data analysis platform 1004 determinesthat current operating conditions exist that cause or potentially causea problem, data analysis platform 1004 may take one or more actions. Forexample, data analysis platform 1004 may send an alert to a remotedevice that the potentially problem-causing operating conditions exist.In another example, data analysis platform 1004 may send a command(e.g., to control platform 1006) to take one or more actions (e.g., opena valve, close a valve, change a flow rate, shutdown, or the like) toprotect the slide valve from being damaged during the existence of thepotentially problem-causing operating condition.

In some aspects, if the data analysis platform 1004 determines that oneor more problems exist or are starting to potentially develop (e.g., thecurrent ΔT differs from another ΔT (e.g., historical ΔTs,manufacturer-standard ΔT, ΔT for another slide valve, etc.)), the system(e.g., data analysis platform 1004 and/or control platform 1006) mayinitiate corrective measures. For example, data analysis platform 1004may send a command to control platform 1006 to take one or morecorrective measures. These corrective measures can include increasingthe pressure in the system, adjusting operating conditions, increasingthe amount of cleanser in the system, increasing purge, sending analert, and/or adding a substance to scrape off the buildup (e.g., walnutshells or coffee beans). Once the corrective measures have beenimplemented, the sensor data (e.g., ΔT, pressure sensor data,temperature sensor data, position sensor data, hydraulic-fluid levelsensor data) again can be measured. If the sensor data (e.g., ΔT,pressure sensor data, temperature sensor data, position sensor data,hydraulic-fluid level sensor data) has returned to its standard state,the corrective measures can cease.

In some aspects, after determining if a problem exists (e.g., if thecurrent ΔT differs from another ΔT), data analysis platform 1004 maysend one or more alerts (e.g., trigger a deviation alarm, send an alertto one or more remote devices (e.g., remote device 1, remote device 2))that the problem exists (e.g., the current ΔT differs from another ΔT).The alert may include information about the potentially sticking slidevalve or the sticking slide valve (e.g., how long the valve takes toopen or close, history of the valve sticking, severity of the valvesticking). The alert may provide information about one or moredetermined correlations between slide valve sticking activity and aparticular operating condition or combination of operating conditions.The alert may include one or more recommendations for adjustments tooperating conditions, adjustments to slide valve positions or settings,or the like.

In some aspects, a remote device may send a command for a particularaction (e.g., a corrective action, such as one of the corrective actionsdescribed above) to be taken, which may or may not be based on thealert. In some aspects, data analysis platform 1004 may send a commandfor a particular action to be taken, whether or not an alert was sent toor a command was sent by the remote device. The command cause one ormore actions to be taken, which may mitigate slide valve sticking,prevent equipment (e.g., slide valve) damage, avoid failure, or thelike. For example, if slide valve sticking rapidly develops, and, basedon analyzing the speed at which the slide valve sticking developsrelative to known failure indicators, data analysis platform 1004determines that the sticking soon will cause a problem over a particularthreshold (e.g., over a cost threshold, over a safety threshold, over arisk threshold, or the like), a shutdown command (e.g., a plantshutdown, a process shutdown, a slide valve shutdown, or the like) maybe sent to cause a shutdown in order to avoid equipment failure,catastrophic failure, slide valve damage, plant damage, or some otherdamage.

In some embodiments, a second slide valve may be incorporated in theplant for backup or emergency use. In some embodiments, the correctiveaction may include opening and/or closing one or more valves in aprocess flow so as to stop the flow to a slide valve that is sticking orstarting to stick and start or divert the flow to the second slidevalve.

Measuring and Determining Hot Spots

One potential problem that slide valves may be subject to is theformation of hot spots. Hot spots may result in weakening and ultimatelyfailure of the material. Hot spots often result from imperfectionsintroduced during slide valve fabrication, but might not be detectableuntil the slide valve is in operation. Hots spots generally form wherethe internals are welded to the body or any section that may containdiscontinuities and the bonnet flange and may result from thecirculation of gas behind the refractory material that coats the slidingvalve components. For example, if hot gas gets behind the protectiverefractory, skin temperatures can grow to exceed the metallurgicallimits.

A typical process may be carried out between about 1275 degrees F. to1450 degrees F. But many of the problems develop due to thermal cyclingwhere the temperature cycles between low and high temperatures (e.g.,between 600 degrees F. and 1275 degrees F.). The extreme change intemperature may cause metal weakening or fatigue. Cracking, deformation,bulging, or other problems may result from a hot spot.

In a cold wall slide valve (such as the one illustrated in FIG. 2), hotspots might form where a stub connects to the wall, and/or at the bonnetsection (e.g., 230 in FIG. 2). If the material behind the wall sags orthere is circulation behind the refractory material between the materialand the wall, a hot spot may result.

Regularly monitoring for hot spots may improve safety and equipmentlife. A thermal gun may be used to measure slide valve temperatures.Alternatively or additionally, a shielded, tube skin thermocoupleassembly may provide a complete temperature profile. Alternatively oradditionally, one or more skin thermocouples may be connected to one ormore locations on the body or shell of the slide valve to monitor forhot spots. For example, a skin thermocouple may be attached near wherethe stub connects to the wall and/or near the bonnet section. In someaspects, when a hot spot has been detected, a skin thermocouple may beattached at or near a known hot spot for continued monitoring of thathot spot.

Alternatively or additionally, fiber optic temperature measurements maybe taken to detect hot spots. Fiber optic cable can be attached to theline or vessel to provide a complete profile of temperatures.

Tomography may also be used to image the slide valve by sections orsectioning, through the use of any kind of a penetrating wave, such asinfrared. One or more thermal cameras may be used (e.g., mounted in oneor more fixed locations around a slide valve, attached to a robot thatmoves around a slide valve, carried by a plant worker) to regularlycapture thermal images of a slide valve. The thermal cameras may bemounted in a configuration such that a combination of images from thethermal cameras allow for viewing all exterior portions of a slidevalve. Alternatively or additionally, thermal cameras may be mounted sothat less than all exterior portions of a slide valve are visible in thethermal images (e.g., thermal imaging might only be taken of areas ofthe slide valve body that are most likely to develop hot spots). One ormore cameras may capture one or more images of the slide valve, whichmay, in some embodiments, allow for convenient comparison of a thermalimage with one or more locations on the slide valve.

Sensor data (e.g., temperature data) may be collected continuously or atperiodic intervals (e.g., every second, every five seconds, every tenseconds, every minute, every five minutes, every ten minutes, everyhour, every two hours, every five hours, every twelve hours, every day,every other day, every week, every other week, every month, every othermonth, every six months, every year, or another interval). Data may becollected at different spots at different intervals. For example, dataat a known hot spot may be collected at a first interval, and data at aspot that is not a known hot spot may be collected at a second interval.Alternatively or additionally, sensor data may be collected based on aparticular event occurrence. For example, a thermal cycle event maytrigger collection of sensor data from one or more sensors.

Sensor data may be collected by a data collection platform 1002. Thesensors may interface with the data collection platform 1002 via wiredor wireless transmissions. The data collection platform 1002 maycontinuously or periodically (e.g., every second, every minute, everyhour, every day, once a week, once a month, etc.) transmit collectedsensor data to a data analysis platform 1004, which may be nearby orremote from the data collection platform 1002.

The data analysis platform 1004 may analyze sensor data to detect newhot spots and/or to monitor existing hot spots (e.g., to determine if anexisting hot spot is growing, maintaining the same size, or shrinking).Temperature data from different dates may be compared to determine ifchanges are occurring. Such comparisons may be made on a monthly,weekly, daily, hourly, or some other basis.

A hot spot may be detected based on a temperature reading for a certainportion of a slide valve body increasing relative to historicaltemperatures for that portion of the slide valve body. For example, if aparticular spot on the slide valve body is historically around 600degrees F., based on regular collected temperature data, but then newtemperature data shows that the particular spot is starting to increasein temperature (e.g., temperature readings are now around 650 degreesF.), the data analysis platform 1004 may determine that a hot spot isstarting to develop.

In some aspects, data from different locations around the slide valvebody may be collectively analyzed. For example, if every location ormost locations on a slide valve body increase in temperature, the dataanalysis platform 1004 may determine that the valve is merely running ata higher temperature, and not that a hot spot is developing. In someaspects, the data analysis platform 1004 may monitor for certain spotsvarying by more than other spots, which may be an indicator of a hotspot. For example, if most locations on a slide valve body increase intemperature by 5%, but a particular spot increases in temperature by10%, the data analysis platform 1004 may determine that a hot spot isdeveloping in that particular spot.

In some embodiments, data from the sensors may be correlated withweather data at the plant. For example, if a rainstorm is currentlyhappening at the plant, the surface temperature, operating temperature,or another temperature of the slide valve might drop. In anotherexample, if a drought and heat wave are currently happening at theplant, the surface temperature, operating temperature, or anothertemperature of the slide valve might increase. The data analysisplatform 1004 may determine, based on the correlation of the weatherconditions to the changes in temperature data, that the changes intemperature of the slide valve are due to weather conditions, and not,e.g., due to a developing hot spot.

In some embodiments, data analysis platform 1004 may determine, based onmonitoring data from one or more slide valves at one or more differentplants, if certain weather conditions and/or other operating conditionsare correlated with development of new hot spots, growth of existing hotspots, or other potential problems with slide valves.

In some embodiments, data from different types of sensors may becross-checked to confirm conclusions drawn from that data, to determinedata reliability, and the like. For example, temperature readings fromskin thermocouples may be compared to temperature readings from athermal imaging camera, thermal topography may be compared tophotographs, or the like.

In some aspects, data analysis platform 1004 may use additional datafrom the slide valve or from other equipment connected to the slidevalve (e.g., in the same plant, in a plant upstream of the plant, etc.)to determine additional information about the hot spot. For example, ifa known hot spot being monitored remains the same size or grows at afirst rate when a first operating condition exists and the known hotspot remains the same size or grows at a second rate when a secondoperating condition exists, the data analysis platform 1004 maydetermine such a correlation by comparing the hot spot data to otherdata. One or more examples of an operating condition may include, e.g.,the plant is operated at a particular efficiency, a particular amount offeed is used, a particular operating temperature of a piece of equipmentupstream of the slide valve is maintained, a particular amount ofcatalyst is used, a particular temperature of catalyst is used, weatherconditions, and the like. In some aspects, a particular operatingcondition or combination of operating conditions may be determined to bemore likely to cause development of new hot spots or growth, stability,or stabilization of existing hot spots.

In some aspects, data analysis platform 1004 may determine if a hot spotis approaching a known damage or failure condition. For example, if aslide valve shell is designed to withstand temperatures up to 800degrees F., and a hot spot is at 775 degrees F. and increasing intemperature, data analysis platform 1004 may determine that the hot spotmay soon cause equipment failure. Data analysis platform 1004 may usehistorical data from the slide valve, data from other slide valves atthe plant, data from other plants, data from a manufacturer,specification data, or other data to determine how a hot spot mightdevelop, grow, stabilize, cause failure, or the like.

If a new hot spot is detected, data analysis platform 1004 may take oneor more actions. For example, data analysis platform 1004 may trigger analert to one or more remote devices (e.g., remote device 1, remotedevice 2). The alert may include information about the hot spot (e.g.,temperature of the hot spot, how hot the hot spot is relative to thesurrounding area, how long the hot spot has been at a particulartemperature, history of the hot spot (e.g., if the hot spot is new orhas been there for an amount of time), severity of the hot spot). Thealert may provide information about one or more determined correlationsbetween hot spot activity and a particular operating condition orcombination of operating conditions. The alert may include one or morerecommendations for adjustments to operating conditions, adjustments toslide valve positions or settings, or the like.

In some aspects, a remote device may send a command for a particularaction to be taken, which may or may not be based on the alert. In someaspects, data analysis platform 1004 may send a command for a particularaction to be taken, whether or not an alert was sent to or a command wassent by the remote device. The command cause one or more actions to betaken, which may mitigate a hot spot, prevent equipment (e.g., slidevalve) damage, avoid failure, or the like. For example, if a hot spotrapidly develops, and, based on analyzing the growth rate of the hotspot relative to known failure temperatures, data analysis platform 1004determines that the hot spot soon will cause a problem over a particularthreshold (e.g., over a cost threshold, over a safety threshold, over arisk threshold, or the like), a shutdown command (e.g., a plantshutdown, a process shutdown, a slide valve shutdown, or the like) maybe sent to cause a shutdown in order to avoid equipment failure,catastrophic failure, slide valve damage, plant damage, or some otherdamage.

In some embodiments, (e.g., if the data analysis platform 1004determines a correlation between one or more operating conditions and apotential problem, such as a higher likelihood to develop new or growexisting hot spots), if the data analysis platform 1004 determines thatcurrent operating conditions exist that cause or potentially cause aproblem, data analysis platform 1004 may take one or more actions. Forexample, data analysis platform 1004 may send an alert to a remotedevice that the potentially problem-causing operating conditions exist.In another example, data analysis platform 1004 may send a command(e.g., to control platform 1006) to take one or more actions (e.g., opena valve, close a valve, change a flow rate, shutdown, or the like) toprotect the slide valve from being damaged during the existence of thepotentially problem-causing operating condition.

Early detection of hot spots may allow for corrective action to be takenbefore equipment failure. Data analysis platform 1004 may send an alertto one or more devices at the plant. The alert may includerecommendations for changes in operating conditions to make, repairs tomake, or the like.

For example, depending on how hot the spot gets, an air ring, a steamring, and/or a water-mist ring (depending on severity of the hot spot)may be installed to correct or ameliorate a hot spot.

In some embodiments, a connection (e.g., a valve, nozzle) may be addedto the body or shell of the valve at the time of fabrication in one ormore locations where hot spots might occur (e.g., near the bonnetsection). If a hot spot is detected, data analysis platform 1004 mayprovide a recommendation to inject a substance (e.g., furmanite) via theconnection to fill or partially fill the void between the wall and theshell, thereby decreasing or inhibiting the gas circulation causing thehot spot.

In some instances, damage because of hot spots might not be fixablewhile the valve is in operation (e.g., while the plant is online);however, it would be beneficial to determine at an early stage if hotspots are forming so that corrective action may be taken to extend thelife of the slide valve. For example, if a corrective action can beimplemented to lessen the severity of the hot spot, it may be possibleto continue operating the valve until the next scheduled plant shutdown,when the slide valve may be further repaired or replaced. In someinstances, data analysis platform 1004 may provide a recommended actionto be taken at a time of a next shutdown. Data analysis platform 1004may store information about the hot spot, and the next time dataanalysis platform 1004 receives information indicating that a plantshutdown is scheduled to happen or is happening, data analysis platform1004 may send an alert or a renewed alert with one or morerecommendations for repairs to make during the shutdown, based on thehot spot data collected.

The data taken from one or more of the various sensors may be correlatedwith weather and environmental data to determine predictive models ofpotential problems in the current slide valve, and/or other slide valvesused in different processes and environments. The data may be taken on aperiodic basis. In some embodiments, more data points may enable betterpredictive outcome (e.g., allowing early prediction of potentialfailures and/or implementation of preventative measures). For example,if catalyst is hindering the movement between the disc and the guides,the guides may be blasted with water or gas to remove the catalyst.

CONCLUSION

Aspects of the disclosure have been described in terms of illustrativeembodiments thereof. Numerous other embodiments, modifications, andvariations within the scope and spirit of the appended claims will occurto persons of ordinary skill in the art from a review of thisdisclosure. For example, one or more of the steps illustrated in theillustrative figures may be performed in other than the recited order,and one or more depicted steps may be optional in accordance withaspects of the disclosure.

What is claimed is:
 1. A system comprising: a condenser; a regenerator;a distillation column; a pump; a slide valve; one or more sensorscomprising a position sensor, the one or more sensors configured tocollect operation information associated with the slide valve; a datacollection platform comprising: one or more processors; a firstcommunication interface in communication with the one or more sensors;and non-transitory computer-readable memory storing executableinstructions that, when executed, cause the data collection platform to:receive sensor data from the one or more sensors, the sensor data fromthe one or more sensors comprising the operation information associatedwith the slide valve; correlate the sensor data from the one or moresensors with metadata comprising time data, the time data correspondingto the operation information associated with the slide valve; andtransmit, to a data analysis platform, the sensor data from the one ormore sensors; the data analysis platform, comprising: one or moreprocessors; a second communication interface; and non-transitorycomputer-readable memory storing executable instructions that, whenexecuted, cause the data analysis platform to: receive, from the datacollection platform, the sensor data from the one or more sensors;analyze the sensor data from the one or more sensors; based on analyzingthe sensor data from the one or more sensors, determine an operatingcondition of the slide valve; and transmit, to a control platform, theoperating condition of the slide valve; and the control platformcomprising: one or more processors; a third communication interface; andnon-transitory computer-readable memory storing executable instructionsthat, when executed, cause the control platform to: receive, from thedata analysis platform, the operating condition of the slide valve; andbased on the operating condition of the slide valve, cause adjustment toa hydraulic pressure associated with the slide valve.
 2. The system ofclaim 1, wherein the non-transitory computer-readable memory of the datacollection platform stores executable instructions that, when executed,cause the data collection platform to: receive the time datacorresponding to the operation information associated with the slidevalve, the time data comprising a start time of a movement of acomponent of the slide valve and a stop time of the movement of thecomponent of the slide valve.
 3. The system of claim 1, wherein thenon-transitory computer-readable memory of the data analysis platformstores executable instructions that, when executed, cause the dataanalysis platform to: receive weather information corresponding toweather at a geographic location of the slide valve; correlate thesensor data from the one or more sensors with the weather informationcorresponding to weather at the geographic location of the slide valve;and determine whether the operating condition of the slide valve isassociated with the weather at the geographic location of the slidevalve.
 4. The system of claim 1, wherein the non-transitorycomputer-readable memory of the data analysis platform stores executableinstructions that, when executed, cause the data analysis platform to:send an alert to a remote device, the alert comprising the operatingcondition of the slide valve.
 5. The system of claim 1, wherein thenon-transitory computer-readable memory of the data analysis platformstores executable instructions that, when executed, cause the dataanalysis platform to: based on the operating condition of the slidevalve, send a message configured to cause an adjustment to a position ofthe slide valve.
 6. The system of claim 1, wherein the one or moresensors comprise a temperature sensor, and wherein the non-transitorycomputer-readable memory of the data analysis platform stores executableinstructions that, when executed, cause the data analysis platform to:receive sensor data comprising temperature information associated withthe slide valve; correlate the temperature information with theoperating condition of the slide valve; and based on the operatingcondition of the slide valve, send a message configured to cause anadjustment to a position of the slide valve.
 7. The system of claim 6,wherein the non-transitory computer-readable memory of the data analysisplatform stores executable instructions that, when executed, cause thedata analysis platform to: determine whether the temperature informationassociated with the slide valve corresponds to a hot spot in the valve;determine a recommendation for correcting the hot spot in the valve; andtransmit, to a remote device, the recommendation for correcting the hotspot in the valve.
 8. A method of plant operation for a plant comprisinga condenser, a regenerator, a distillation column, a pump, and a slidevalve, the method comprising: at a data collection platform comprisingone or more processors, memory, and a communication interface incommunication with one or more sensors comprising a position sensorassociated with the slide valve: receiving sensor data from the one ormore sensors, the sensor data comprising operation informationassociated with the slide valve, the sensor data correlated withmetadata comprising time data, the time data corresponding to theoperation information associated with the slide valve; analyzing thesensor data from the one or more sensors; based on analyzing the sensordata from the one or more sensors, determining an operating condition ofthe slide valve; and transmitting, to a control platform, a messagecomprising the operating condition of the slide valve, the messageconfigured to cause an adjustment to a hydraulic pressure associatedwith the slide valve.
 9. The method of claim 8, further comprising:receiving the time data corresponding to the operation informationassociated with the slide valve, the time data comprising a start timeof a movement of a component of the slide valve and a stop time of themovement of the component of the slide valve.
 10. The method of claim 8,further comprising: receiving weather information corresponding toweather at a geographic location of the slide valve; correlating thesensor data from the one or more sensors with the weather informationcorresponding to weather at the geographic location of the slide valve;and determining whether the operating condition of the slide valve isassociated with the weather at the geographic location of the slidevalve.
 11. The method of claim 8, further comprising: sending an alertto a remote device, the alert comprising the operating condition of theslide valve.
 12. The method of claim 11, further comprising: receiving,from the remote device, a command to cause the adjustment to thehydraulic pressure associated with the slide valve.
 13. The method ofclaim 8, wherein the one or more sensors comprise a temperature sensor,and wherein the method further comprises: receiving sensor datacomprising temperature information associated with the slide valve;correlating the temperature information with the operating condition ofthe slide valve; and based on the operating condition of the slidevalve, sending a message configured to cause an adjustment to a positionof the slide valve.
 14. The method of claim 13, further comprising:determining whether the temperature information associated with theslide valve corresponds to a hot spot in the valve; determining arecommendation for correcting the hot spot in the valve; andtransmitting, to a remote device, the recommendation for correcting thehot spot in the valve.
 15. A method of operation for a refinerycomprising a condenser, a regenerator, a distillation column, a pump,and a slide valve, the method comprising: at a data collection platformcomprising one or more processors, memory, and a communication interfacein communication with one or more sensors comprising a position sensorassociated with the slide valve: receiving sensor data from the one ormore sensors, the sensor data comprising operation informationassociated with the slide valve, the sensor data correlated withmetadata comprising time data, the time data corresponding to theoperation information associated with the slide valve; analyzing thesensor data from the one or more sensors; based on analyzing the sensordata from the one or more sensors, determining an operating condition ofthe slide valve; and transmitting, to a control platform, a messagecomprising the operating condition of the slide valve, the messageconfigured to cause an adjustment to a hydraulic pressure associatedwith the slide valve.
 16. The method of claim 15, further comprising:receiving the time data corresponding to the operation informationassociated with the slide valve, the time data comprising a start timeof a movement of a component of the slide valve and a stop time of themovement of the component of the slide valve.
 17. The method of claim15, further comprising: receiving weather information corresponding toweather at a geographic location of the slide valve; correlating thesensor data from the one or more sensors with the weather informationcorresponding to weather at the geographic location of the slide valve;and determining whether the operating condition of the slide valve isassociated with the weather at the geographic location of the slidevalve.
 18. The method of claim 15, further comprising: sending an alertto a remote device, the alert comprising the operating condition of theslide valve.
 19. The method of claim 15, wherein the one or more sensorscomprise a temperature sensor, and wherein the method further comprises:receiving sensor data comprising temperature information associated withthe slide valve; correlating the temperature information with theoperating condition of the slide valve; and based on the operatingcondition of the slide valve, sending a message configured to cause anadjustment to a position of the slide valve.
 20. The method of claim 19,further comprising: determining whether the temperature informationassociated with the slide valve corresponds to a hot spot in the valve;determining a recommendation for correcting the hot spot in the valve;and transmitting, to a remote device, the recommendation for correctingthe hot spot in the valve.